Abstract
This paper falls within the context of diagnosis of rotating machines in speed variable regime. Based on simulation signals, this work has the purpose to find relevant indicators for the diagnosis of gear transmissions in a variable regime. Two indicators are proposed; the first indicator is the RMS value applied to the vibration signal divided by its corresponding instantaneous frequency. The second is the normalised gear frequency by averaging speed. The gear frequency and averaging speed are estimated from the spectrogram. To test the proposed indicators simulate signals have been used. These signals are the results of a dynamic modelling of the gears transmission and are calculated by using the Newmark integration diagram. This dynamic modelling takes into account the eccentricity defect.
Highlights
In the other hand, many researchers have developed techniques allowing the gear defects detection and diagnosis, based on the vibration signals analysis [6,7,8,9,10,11,12,13,14]
The gears are assimilated to rigid cylinders connected by a mesh stiffness which represents the elastic connection between teeth
The eccentricity defect is due to the fact that the pitch circles of the wheels do not have their center on the rotation axis of the corresponding wheel
Summary
Many researchers have developed techniques allowing the gear defects detection and diagnosis, based on the vibration signals analysis [6,7,8,9,10,11,12,13,14]. The gear transmissions defects monitoring is more complicated when the operating parameters of systems are variable especially for the speed and for the load This kind of operating regime is prevalent in industry, for example the tramway, plane motors, wind turbine etc. Under these non-stationary operations, the amplitude and frequency components are always changing because of speed variation (or load variation) This affects clearly the classical diagnosis tools, which are not suitable for nonstationary analysis, and a potential fault can be masked. In reference [15], the authors present the results of an algorithm of vibration statistical analysis, applied on a test bench which simulates the wind turbine machine functioning under variable speed and load conditions.
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
